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The successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex. As the pandemic shifted consumer preference in favour of digital platforms, more and more fast-moving consumer goods (FMCG) companies were confronted with multiple strategies and choices of an appropriate distribution channel to ensure smooth delivery of raw materials and products. The present study aims to study this shift and its implications in the Indian context.

A mix-method approach, integrating quantitative and qualitative analysis, is employed to investigate the factors influencing the selection of distribution channels amongst general trade, modern trade, e-commerce and hyperlocal for FMCG companies in India. The first phase of the study uses exploratory factor analysis (EFA), followed by the application of analytical hierarchy process (AHP) approach in a fuzzy environment to realise the priority weights and ranking of the identified factors. Finally, sensitivity analysis is performed to confirm the robustness of the fuzzy analytical hierarchy process (FAHP) outcomes.

The study revealed that modern trade has emerged as the most favoured channel in the post-pandemic Indian economy. It has the potential to disrupt general trade. The study also revealed that the hyperlocal delivery model is not economically viable, and the partnership of FMCG companies with these applications is at best a short-term solution. However, it must be submitted that due to its sheer capability to ensure quick deliveries within a confined geographic area, hyperlocal delivery will gain momentum with the advancement of technology.

This study can be seen as the first attempt to investigate the issues related to the selection of the distribution channels in the FMCG sector of India using multi-criteria decision-making technique (MCDM).

The unmanned ground vehicle (UGV) described in this manuscript is a robot designed by the authors to map the underground mine environments. The UGV works to develop a computational intelligence-based cyber-physical system (CPS)-based analytical framework for mining operations. The UGV demonstrated excellent semi-autonomous navigation capabilities in the absence of GNSS signals. The UGV has a suite that works in unison to provide relevant information. These sensors are integrated to form a robust sensor fusion-based architecture, creating a CPS with a wide range of capabilities such as data acquisition and navigation in challenging underground environments. UGVs can be used to enhance the efficacy of safety inspections, rescue during underground emergencies and assist miners in hazardous conditions.

In this research, an UGV was constructed whose operations are enabled by sensors including a D415i Red Blue Green (RGB) depth camera, a LiDAR, a FLIR C5 infrared camera and smart air quality sensors. This sensor fusion-based architecture forms a CPS. Data obtained remotely are processed by deep learning algorithms to achieve overall capabilities such as real-time image analysis for miner identification, object detection, posture analysis and identifying threats of roof falls and overhangs. Simultaneous localization and mapping (SLAM) algorithms create a 3D map, facilitate autonomous navigation and build a decision support system for delivering mine rescue support.

The aim of this study is to include this capacity in training situations when it has been validated and authorized by the Directorate General of Mines Safety (DGMS) Indian government regulatory agency for safety in mines and oil fields. The longwall demo mine, at IIT (ISM) is being used as the site of the first operations. Once approved by the respective enforcement agencies, this technology and the accompanying rescue and training process can be used in underground operations.

In fact, this paper is the first attempt at remotely operated UGVs based on CPSs, the CPS–UGV in Indian mine conditions, so as to revolutionize Indian mines based on the idea of Industry 4.0.